Note: The job is a remote job and is open to candidates in USA. IS3 Solutions is seeking a Data Engineer, GenAI Data Systems professional to build and operate reliable data systems supporting large-scale datasets and annotation workflows. The role focuses on data modeling, ETL and ELT pipelines, Databricks workloads, dashboards, telemetry, automation, and cross-functional delivery across the full lifecycle of data solutions.
Responsibilities
- Build and maintain data pipelines and processing frameworks supporting dataset creation, annotation workflows, and large scale data movement across batch and incremental processing patterns
- Design and maintain data models and pipelines for large scale multimodal datasets including text, image, video, and audio
- Design and support high volume logging and telemetry systems with a focus on operational efficiency, monitoring, and troubleshooting
- Develop and maintain dashboards, reports, metrics, and alerting solutions that track throughput, quality, cost, and overall program health
- Design and maintain data models, schemas, databases, lakehouse environments, dimensional models, and reporting structures
- Build, optimize, and support Databricks workloads including transformations, orchestration, governance, and performance tuning
- Implement data quality validation, monitoring, and alerting mechanisms to improve reliability and trust in data assets
- Develop and maintain workflows that move data into and out of annotation platforms including preprocessing, post processing, validation, and delivery of annotated datasets
- Support engineering needs related to annotation project user interfaces, testing activities, and quality assurance initiatives
- Develop backend services, automation tools, and production software using Python and established engineering best practices
- Troubleshoot complex technical issues spanning multiple systems and identify root causes to implement sustainable solutions
- Partner with business, engineering, and operational teams to gather requirements, communicate progress, and document systems and procedures
- Independently evaluate ambiguous requests, design solutions, manage priorities, and execute cross functional initiatives
- Integrate pipelines and applications with cloud platforms, storage systems, and data annotation technologies while ensuring strong observability and reliability
Skills
- • Bachelor's Degree in Computer Science, Engineering, or a related field, or equivalent professional experience
- • Four or more years of professional experience in Data Engineering or a related technical discipline
- • Proven experience designing, building, and operating production ETL and ELT pipelines supporting large and complex datasets
- • Strong proficiency in SQL and Python
- • Experience with version control systems, testing frameworks, and continuous integration and continuous deployment practices
- • Experience with workflow orchestration tools such as Airflow, Dagster, Databricks Jobs, or similar platforms
- • Experience designing and maintaining data models, databases, warehouses, or lakehouse architectures
- • Experience supporting high volume logging or telemetry solutions
- • Experience building dashboards, reports, metrics, and alerting solutions
- • Hands on experience with Databricks, Spark, Delta Lake, or similar large scale data platforms
- • Experience working with AWS, Azure, or Google Cloud Platform
- • Demonstrated proficiency using AI tools for coding and data related workflows while applying strong engineering fundamentals and technical judgment
- • Strong problem solving and troubleshooting skills
- • Excellent written and verbal communication skills
- • Ability to work independently, manage competing priorities, and proactively communicate status and risks
- • Eight or more years of Data Engineering or Analytics Engineering experience
- • Experience supporting human in the loop annotation programs and data labeling workflows
- • Direct experience with SuperAnnotate
- • Experience supporting machine learning, Large Language Model, or Vision Language Model training data pipelines
- • Experience working with large scale multimodal datasets including text, image, video, and audio
- • Experience with JavaScript, TypeScript, HTML, or full stack application development supporting internal tools and workflow applications
Benefits
- Remote and onsite work models
Company Overview